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A New 3D-Regular Shaped Geometry-Based MIMO Channel Model for Vehicle-to-Vehicle communications in Rectangular Tunnel 1

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14th international conference on Computational Collective Intelligence (ICCCI)

作者： Chebil, Jalel Zormati, Hanene Mansour, Ali Ben Mabrouk, Ismail Tahar, Jamel Bel Hadj Univ Sousse Dept Technol & Transport Engn NOCCS Lab ISTLS Sousse Tunisia Univ Sousse Dept Elect Engn NOCCS Lab ENISO Eniso Tunisia ENSTA Bretagne Brest France Univ Durham Dept Engn Durham England

ISBN: (数字)9783031160141

ISBN: (纸本)9783031160141;9783031160134

the intelligent transportation systems have attracted the attention of many researchers and developers in the last few decades in order to make the exploitation of transportation networks be safer, more coordinated, and smarter. Channel modeling for vehicle-to-vehicle (V2V) communication is one of the related research topics that are being investigated in this field. In this paper, a three-dimensional wideband regular shaped geometry based channel model for multiple-input and multiple-output V2V communication channel is proposed for rectangular tunnel environments. A two semi-circular geometry is adopted to describe moving vehicles around transmitter and receiver, and a cuboid model is employed to depict scatterers located on internal surfaces of the tunnel walls. Using this channel model, the channel characteristics including space time correlation function, frequency correlation function and auto-correlation function are determined and simulated numerically. then, the results are compared with the derived statistics from Avazov et al. and Zhou et al. methods to prove the efficiency of the proposed model.

关键词： Channel model MIMO channel Rectangular tunnel Vehicle-to-vehicle communication

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Integrated Waveform Design of Radar and communication systems for the Single Transmitter Multiple Receivers System 14

Integrated Waveform Design of Radar and Communication System...

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14th international conference on Signal Processing systems, ICSPS 2022

作者： Zhou, Xianxin Chen, Jun Wang, Fei College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Key Laboratory of Radar Imaging and Microwave Photonics of the Ministry of Education Nanjing China College of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9798350336313

Compared with a monostatic radar system, a Single Transmitter Multiple Receivers (STMR) system has the advantages of high detection accuracy, long detection distance, and good Low Probability of Intercept (LPI) performance. the integrated radar and communication system has been a research hotspot because it can significantly reduce system volume and power consumption. To realize the radar and communication integration of the STMR system, an integrated waveform design method is proposed in this paper. Firstly, the necessary source information for successfully cooperative detection is designed and preprocessing is applied to improve communication effectiveness and reliability. Secondly, the integrated waveform based on the spread spectrum technique and Minimum Shift Keying (MSK) modulation is designed to enable the signal to have the anti-interference and anti-intercept ability, which is called the DSSS-FH-MSK signal. the coded sequence goes through the Direct Sequence Spread Spectrum (DSSS), and the sequence after spreading spectrum is modulated by MSK, then the frequency of the carrier hops randomly by using the Hopping Frequency (HF) technique. Simulation results indicate that the DSSS-FH-MSK signal has a thumbtack type Cross Ambiguity Function (CAF) which means it has good estimation performance in the STMR system. Additionally, LPI evaluation methods are employed to verify that the designed signal has excellent LPI performance. © 2022 IEEE.

关键词： Transmitters

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Gyms Customer Loyalty Using the Logistic Regression Algorithm Technique

Gyms Customer Loyalty Using the Logistic Regression Algorith...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Joaquin Moreno Muñoz Miguel Ramirez Osorio Ciro Rodriguez Diego Rodriguez Pedro Lezama Yuri Pomachagua Software Engineering Department Universidad Nacional Mayor de San Marcos UNMSM Lima Peru Medicine Faculty of Health Sciences Universidad Peruana de Ciencias Aplicadas UPC Lima Peru Systems Engineering Department Universidad Nacional Federico Villarreal UNFV Lima Peru

ISBN: (纸本)9781665487726

the objective of this work is to implement the logistic regression technique in datasets of gyms to identify and make a respective analysis for a correct segmentation of clients and, in this way, maximize the possibility of retaining clients; this will also allow us to rule out wrong decisions and incorrect assumptions, in addition to optimizing management according to customer data, which will be vital for a correct loyalty of gym users. the precision calculated the loyalty by the logistic regression algorithm considering important factors such as the rate of abandonment.

关键词： Support vector machines Neural networks Prediction algorithms Object recognition communication networks Random forests Computational intelligence

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Optimizing Waste Management through Intelligent Machine Learning systems: A Comparative Study

Optimizing Waste Management through Intelligent Machine Lear...

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international conference on Computing and Networking Technology (ICCNT)

作者： Nandikante Shravani S. Vigneshwari Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

the purpose of this research study is to examine the use of intelligent machine learning systems in the process of optimising waste management practises. Several other approaches, such as Artificial Neural networks, K-nearest neighbours, Logistic regression, Decision Trees, Support Vector Machine, and Random Forest, are being investigated as potential ways to improve the currently utilised waste management paradigm. On the other hand, with the implementation of algorithms for machine learning, these measures saw a huge improvement. the use of these methods brought in a remarkable increase in classification accuracy, which reached 92.349%, and a recall rate of 91.04%. this significant improvement in performance demonstrates the usefulness of machine learning in the process of optimising waste management. the Random Forest classifier proved to be the strategy that offered the best results after being compared to the other approaches investigated. In particular, the use of this classifier helped to improve the accuracy of estimates for the amount of time required to empty recycling containers. In a nutshell, the purpose of this study article was to demonstrate how effective intelligent machine learning systems can be in improving existing waste management procedures.

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Competency Model for Programming Courses in Information Technology Education (ITE) Programs from Industry Perspective: A Delphi Method 14

Competency Model for Programming Courses in Information Tech...

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14th IEEE international conference on Humanoid, Nanotechnology, Information Technology, communication and Control, Environment, and Management, HNICEM 2022

作者： Goh, Joselito Eduard E. Mojado, Catherine V. Manaligod, Hector John T. De la Salle - College of Saint Benilde Information Systems Program Manila Philippines De la Salle - College of Saint Benilde Computer Application Program Manila Philippines

ISBN: (纸本)9781665464932

this study aimed to develop a competency model for software development courses in ITE programs as perceived by the IT industry in the Philippines in the new normal. A review of previous studies revealed existing software engineering competency models being referenced by the IT industry along with the Commission on Higher Education (CHED) General Education Curriculum (GEC) being referenced by the academe. However, things drastically changed during this global pandemic which may have affected these current standards. thus, this study aimed to determine the current competency needs in the IT industry in the new normal in relation to the programming courses being offered by the ITE programs in the Philippines;A mixed method three-round Delphi technique was used to solicit a unified expert opinion from the point of view of nine (9) IT industry experts in the Philippines. Twenty-three (23) technical skills and eleven (11) soft skills were extracted from online interviews using thematic analysis. Out of 23 technical skills, nineteen (19) have consensus. the findings produced a competency model for software development courses in the new normal consisting of must-have technical skills, game-changer technical skills, and must-have soft skills. the must-have technical skills include Web Development, Cyber Security, Cloud Computing, Agile Project Management, Mobile Development, and DevOps. the game changer technical skills include Data Science and Data Analytics, Artificial Intelligence and Machine Learning, the Internet of things, and Research and Development. And the must-have soft skills include communication skills, Results-Oriented, and Collaboration skills. © 2022 IEEE.

关键词： Data Analytics

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Smart Monitoring of High-Performance KY Converter in IoT-Enabled Electric Vehicle systems 14

Smart Monitoring of High-Performance KY Converter in IoT-Ena...

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14th IEEE international conference on communication systems and Network Technologies, CSNT 2025

作者： Rathika, N. Ramya, R.R. Ganga, P. Patwa, Sharda Balaji, V. Sivarajan, S. Department of Electrical and Electronics Engineering 6116-Mahendra Institute of Technology Mallasamuthiram Namakkal India Department of Information Technology University College Of Engineering Nagercoil India Department of Electrical and Electronics Engineering Annapoorana Engineering College Tamilnadu India Department of Electrical Engineering Medi-caps University Madhyapradesh Indore India Department of Electrical and Computer Engineering MAI-NEFHI College of Engineering and Technology Eritrea Department of Electrical and Electronics Engineering Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Tamil Nadu Chennai India

ISBN: (纸本)9798331531935

the smart Electric Vehicle (EV)-Improved KY Converter monitoring system, which is Internet of things (IoT)based, provides an advanced method for improving the dependability and efficiency of EV power systems. By utilizing IoT technology, this system keeps a close eye on the enhanced KY converter's efficiency, which is essential for controlling power conversion in electric vehicles. the Adaptive Neuro-Fuzzy Inference System (ANFIS) based Maximum Power Point Tracking (MPPT) effectively operates the system at maximum power level with fast response and low oscillations. It effectively optimizes energy conversion from Photo Voltaic (PV) by dynamically modifying to the operating point under varying environmental conditions. the deployment of this intelligent monitoring system is expected to yield notable progress in the administration and functioning of electric vehicle power systems, hence augmenting the general sustainability of electric-powered transportation. the proposed system is implemented in MATLAB, employing its sophisticated simulation capabilities to analyse the PV system. this simulation framework enables for the testing and validation of key performance metrics of 98% efficiency exhibiting in boosting power extraction and grid stability. © 2025 IEEE.

关键词： Fuzzy neural networks

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An Ensemble Learning-Based Cyber-Attacks Detection Method of Cyber-Physical Power systems 7

An Ensemble Learning-Based Cyber-Attacks Detection Method of...

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7th IEEE international conference on Advanced Robotics and Mechatronics

作者： Lu, Kang-Di Wu, Zheng-Guang Zhejiang Univ Inst Cyber Syst & Control Natl Lab Ind Control Technol Hangzhou 310027 Peoples R China

ISBN: (数字)9781665483063

ISBN: (纸本)9781665483063

the cyber-physical power system (CPPS) is evolved from the traditional power system by the deployment of information networks with control systems, computational units, and communication networks. However, their integration into CPPS introduces new challenges in maintaining security. Various malicious cyber-attacks are drawn much attention recently after the discovery of the impact on CPPS state estimation. thus, it is of great significance for operators to detect cyber-attacks and identify the types of attacks in CPPS to make decisions appropriately. this problem can be viewed as a multi-class classification problem from the perspective of machine learning. Accordingly, this paper proposes an ensemble learning-based cyber-attacks detection model for CPPS state estimation. In the proposed model, we use the subspace features and then send the data to the classifier for ensemble, where decision trees and random vector functional link networks are introduced as the basic classifier. the proposed model is validated by employing simulated data on IEEE 14-bus and 30-bus systems. Simulation results demonstrate the performance of the proposed cyber-attacks detection model.

关键词： Cyber-physical power systems cyber-attacks ensemble learning multi-class classification

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Evaluation of Voice Service in LEO communication with 3GPP PUSCH Repetition Enhancement

Evaluation of Voice Service in LEO Communication with 3GPP P...

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14th Annual Summit and conference of the Asia-Pacific-Signal-and-Information-Processing-Association (APSIPA ASC)

作者： Liu, Shou-Hong Liu, Chun-Tai Chou, Wei-Hung Pan, JenYi Natl Chung Cheng Univ Dept Commun Engn Chiayi Taiwan Natl Chung Cheng Univ Adv Inst Mfg High Tech Innovat Chiayi Taiwan Ind Technol Res Inst Hsinchu Taiwan

ISBN: (数字)9786165904773

ISBN: (纸本)9786165904773

In recent years, 3GPP (3rd generation partnership project) has studied and developed the standards for Non-terrestrial networks (NTN). One of the newest working items for NTN is coverage enhancements. In this paper, we construct the NTN channel described in 3GPP. Moreover, we summarize the NTN channel model and current coverage enhancements. Since the scenario of NTN is very different from the traditional terrestrial network systems, we also summarize the challenges and phenomena of the NTN. To reach the high communication quality of voice over internet protocol (VoIP) service in NTN, we evaluate the performance and discuss the benefit of the PUSCH repetition technique in the NTN low Earth orbit (LEO) scenario.

关键词： NTN VoIP PUSCH repetition satellite communication

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Enhancing Metabolomics Pathway Prediction with Sequential Graph Convolutional Network

Enhancing Metabolomics Pathway Prediction with Sequential Gr...

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international conference on communication systems and Network Technologies (CSNT)

作者： Bineesh Moozhippurath Jayapandian Natarajan Department of Computer Science and Engineering Christ University Bangalore India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Metabolomics is a powerful tool for the understanding of biological systems by analysis of metabolites and their related pathways. Prediction of metabolic pathways is still one of the most challenging tasks because of the complexity of molecular structures and graph-structured metabolomics data. this article presents a robust framework using Graph Convolutional networks (GCNs) to address the challenges. the methodology proposed includes first preprocessing through metabolite identification by mass spectrometry, and then it utilizes feature extraction through the RDKit library. the objective of the research is aim to metabolic pathway prediction using machine learning algorithm. Complex patterns and relationships are captured from the SMILES representation through the molecular graphs constructed and passed on for the GCN model to learn structured data. ReLU activation functions have been employed within a three-layer sequential GCN architecture that enables it to deliver highly accurate results while ensuring that they are understandable as well. the proposed sequential GCN Model was evaluated on the KEGG dataset with an accuracy of 98.00%, precision of 92.10%, and recall of 93.02%. the performance of these metrics is well beyond traditional approaches such as KNN, ensemble logistic regression, and other GCN based approaches. thus, this work brings GCN based approaches closer to revolutionizing metabolic pathway prediction and the advancement of the metabolomics field.

关键词： Metabolomics Accuracy Translation Graph convolutional networks Neural networks Biological systems Predictive models Feature extraction Libraries Complexity theory

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Sustainable Substrate Design for High-Performance Wi-Fi Antennas in Green Electronics

Sustainable Substrate Design for High-Performance Wi-Fi Ante...

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international conference on communication systems and Network Technologies (CSNT)

作者： Niketan Kumar Mishra Deepak Sen Rana Pratap Singh Rajput Varun Rajput Lakshmi Narain College of Technology & Science Bhopal Madhya Pradesh India Lakshmi Narain College of Technology Excellence Bhopal Madhya Pradesh India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Microstrip patch antennas are important parts of modern wireless communication systems because of their compact size, high efficiency, and versatility. In this paper, the effect of the properties of the substrate material on the performance of coaxial-feed rectangular microstrip patch antennas operating within the Wi-Fi band (2.4–2.485 GHz) is investigated. A comparative analysis was thus carried out on substrates such as FR-4 and RT Duroid 5870 using CST Studio Suite, evaluating gain, directivity, bandwidth, and return loss. this shows that low dielectric substrates, such as those of Rogers 5870, offer better performance since they provide optimal impedance matching, increased gain, and least return loss, thereby recommended for high-frequency applications. this study underlines the importance of substrate optimization in designing energy-efficient and green antennas for next-generation technologies such as 5G, IoT, and wireless sensor networks in the context of green electronics and sustainable communication systems.

关键词： Green electronics 5G mobile communication Patch antennas Dielectric losses Microstrip antennas Bandwidth Energy efficiency Manufacturing Substrates Wireless fidelity

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